# Package sarima pd \<- packageDescription("sarima") lb \<- library(help="sarima", character.only=TRUE) pd$Title pd$Description package ## Details There is a large number of packages for time series modelling. They provide a huge number of functions, often with similar or overlapping functionality and different argument conventions. One of the aims of package `sarima` is to provide consistent interface to some frequently used functionality. In package `sarima` a consistent naming scheme is used as much as possible. Names of functions start with a lowercase letter and consist of whole words, acronyms or commonly used abbreviations. In multiword names, the second and subsequent words start with capital letters (camelCase). Only the first letter in acronyms is capitalised, e.g. Arma stands for ARMA. Formal (S4) classes follow the same rules but the first letter of the first word is capitalised, as well. For example, the functions that compute autocorrelations, autocovariances, partial autocorrelations are called `autocorrelations`, `autocovariances`, and `partialAutocorrelations`, respectively. Moreover, they recognise from their argument(s) what exactly is needed. If they are given times series, they compute sample autocorrelations, etc; if they are given model specifications, they compute the corresponding theoretical properties. This is work in progress, see also the vignette(s). ## Author(s) pd$Author Maintainer: pd$Maintainer ## References \insertRef boshnakov1996aismsarima \insertRef BoshnakovHalliday2022parcorsarima \insertRef BrockwellDavis1991sarima \insertRef FrancqZakoian2010garchsarima \insertRef Li2004diagnosticsarima \insertRef McLeodYuKrougly2007sarima ## See Also `ArmaModel` `autocorrelations` ## Examples ```r ## simulate a white noise ts (model from Francq & Zakoian) n <- 5000 x <- sarima:::rgarch1p1(n, alpha = 0.3, beta = 0.55, omega = 1, n.skip = 100) ## acf and pacf ( x.acf <- autocorrelations(x) ) ( x.pacf <- partialAutocorrelations(x) ) ## portmanteau test for iid, by default gives also ci's for the acf under H0 x.iid <- whiteNoiseTest(x.acf, h0 = "iid", nlags = c(5,10,20), x = x, method = "LiMcLeod") x.iid x.iid2 <- whiteNoiseTest(x.acf, h0 = "iid", nlags = c(5,10,20), x = x, method = "LjungBox") x.iid2 ## portmanteau test for garch H0 x.garch <- whiteNoiseTest(x.acf, h0 = "garch", nlags = c(5,10,20), x = x) x.garch ## plot methods give the CI's under H0 plot(x.acf) ## if the data are given, the CI's under garch H0 are also given. plot(x.acf, data = x) ## Tests based on partial autocorrelations are also available: plot(x.pacf) plot(x.pacf, data = x) ## Models ## AR ( ar2a1 <- ArModel(ar = c(-0.3, -0.7), sigma2 = 1) ) autocorrelations(ar2a1, maxlag = 6) partialAutocorrelations(ar2a1, maxlag = 6) autocovariances(ar2a1, maxlag = 6) partialVariances(ar2a1, maxlag = 6) ## see examples for ArmaModel() ```

sarima-package